This activity has benefited from input from faculty educators beyond the author through a review and suggestion process.

This review took place as a part of a faculty professional development workshop where groups of faculty reviewed each others' activities and offered feedback and ideas for improvements. To learn more about the process On the Cutting Edge uses for activity review, see http://serc.carleton.edu/NAGTWorkshops/review.html.

This activity was selected for the On the Cutting Edge Exemplary Teaching Collection

Resources in this top level collection a) must have scored Exemplary or Very Good in all five review categories, and must also rate as “Exemplary” in at least three of the five categories. The five categories included in the peer review process are

Summary

In this exercise, students process LiDAR data for the Hamilton College campus area to determine accurate elevations of wellheads of sampling wells on campus. Students use both GPS readings and orthophotos to determine wellhead locations and combine those with water levels, casing heights, and wellhead elevations to interpolate a groundwater surface under the campus and portray the groundwater in ArcScene. They also learn how to use Model Builder. You might also be interested in our Full GIS course with links to all assignments. You might also be interested in our webinar for the NYS GIS Association on A Simple Example of Working with LiDAR using ArcGIS and 3D Analyst.

Time required for students to complete the assignment:
One week of class/lab plus homework

Goals

GIS/remote sensing techniques students learn in this assignment
Converting raw .las files to multipoint files; building a terrain for first and last returns; converting a terrain to an elevation raster; downloading data from a GPS unit and creating a shapefile; drawing a line in a specific direction for a specific distance; going to a specific X-Y coordinate and adding a point; editing a shapefile, including adding a point with coordinate values, deleting a record, adding fields (and determining field type, precision and scale), calculating geometries, and doing calculations using the Field Calculator; extracting values to points; using interpolation to create a raster from a set of points and viewing it in ArcScene; using Model Builder.

Other content/concepts goals for this activity

Higher order thinking skills goals for this activity
quality assessment of all data and an evaluation of the validity of various interpolation techniques; recommendation for where the next well should be drilled to more accurately define the water table beneath campus.

Description of the activity/assignment

In this six-part exercise, students process LiDAR data for the Hamilton College campus area to develop first return and bare earth terrains and use the LiDAR data to determine accurate elevations of wellheads of sampling wells on campus. They use both GPS readings and orthophotos to determine wellhead locations and combine those with water levels, casing heights, and wellhead elevations to interpolate a groundwater surface under the campus and portray it in ArcScene. Students then develop a model in Model Builder for processing LiDAR data.

Exercise 8a: In this homework assignment, students download and prep the LiDAR data set so that they are ready to go at the start of class (downloadable below). They also explore that LAS files are, use LASTools (link in the assignment) to get information about their LiDAR data sets, and use the Point File Information Tool in ArcGIS to explore their LiDAR data bit more

Exercise 8b: In this class/lab activity, students process the LiDAR point cloud data using ArcGIS by converting the point cloud data to a multipoint file (which ArcGIS can read), and building a series of terrains (multi-resolution TINs). By creating four different TINs, they explore the differences in TINs created from All Returns, First Returns, Last Returns, and Class 2 (ground) returns). They then convert the terrains to rasters and create hillshades for each set of returns and compare the hillshades with their orthophoto data.

Exercise 8c: This is an outdoor class exercise in which students collect GPS data for the locations of wellheads for a number of sampling wells, on campus. Because of the locations of some of the wells, students need to learn how to do offset GPS as well. Students also have experience with a very cool real-time demo of the accuracy of GPS readings, and it gives us a chance to revisit the classroom mapping exercise that we did at the very beginning of the semester. Part of this outdoor lab also involves "field checking" the LiDAR first and last returns (DSM and DTM) that the students created, and they take printouts of both into the field with them to "ground truth" the models. This is a wonderful aspect of this exercise – sounds silly, but it is really really useful to have students take printouts into the field, have them find the features in the DSM and DTM, and decide if anything they are seeing are artifacts.

Exercise 8d and 8e. In these two class/lab exercises, students download their GPS data and create an accurate shapefile showing the locations of the wells. This isn't entirely straightforward, because it involves offset GPS for some wells, and, for others, the orthophotos provide better locations than the GPS does. This involves editing the shapefile created from the GPS data. Students then take the elevations determined from the LiDAR data and combine those with casing height and water depth data (from our hydrogeologist) and use the Field Calculator to determine the elevation of the water table in each well. Students then extract values to points (determine the elevations of points in a shapefile using the elevation data in the raster data set). Once they have a set of points representing the water table, they use interpolation to create a raster from the points. This lets them create a visualization of the water table beneath the campus. They then have to choose (and defend) a location for the next well that would help better define the water table beneath campus.

Exercise 8f. Processing LiDAR point cloud data involves multiple steps that lend themselves well to Model Builder. In this final portion of the exercise, students create a model in Model Builder to process LiDAR point cloud data to create a DTM (digital terrain model) plus a hillshade.

Determining whether students have met the goals

Students are evaluated on their homework preparations, on their evaluation of data quality and validity of their water table model, on their recommendation for the location of a new well, and the success of their Model Builder model.More information about assessment tools and techniques.

URLs and References

Links to all data except the LiDAR data are provided in the exercises themselves. The LiDAR data are available for download below (special thanks to Jeffrey Quackenbush, Oneida County Planning Office, for allowing us to share these data).

Download teaching materials and tips

Activity Description/Assignment: This 2011 version of the exercise(Zip Archive 4.4MB Apr21 11) is written for ArcGIS 10 but will work with ArcGIS 9.3 (screen shots are a little different, but it works OK in 9.3).

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Barb Tewksbury, Hamilton College

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This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

Provenance

Barb Tewksbury, Hamilton College

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This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

Provenance

Barb Tewksbury, Hamilton College

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This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

Provenance

Reuse

This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.

Provenance

Barb Tewksbury, Hamilton College

Reuse

This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.